Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.ypmed.2022.107298 http://hdl.handle.net/11449/248985 |
Resumo: | The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%–32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%–16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%–145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes. |
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Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 casesCOVID-19EpidemiologyInequalities in healthThe study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%–32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%–16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%–145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.Programa de Pós-graduação em Saúde Coletiva Universidade Federal de Santa Catarina, SCFaculdade de Ciências Médicas da Santa Casa de São Paulo, SPInstituto de Física Teórica Universidade do Estado de São Paulo, SPUniversidade Federal da Fronteira Sul, Campus Chapecó, SCHarvard Center for Population & Development Studies Harvard UniversityUniversidade Federal de Santa Catarina (UFSC)Faculdade de Ciências Médicas da Santa Casa de São PauloUniversidade do Estado de São PauloUniversidade Federal da Fronteira SulHarvard UniversityBoing, Antonio FernandoBoing, Alexandra CrispimVeras, Maria Améliade Lacerda, Josimari Telinoda Silva, Rafael Lopes PaixãoBarbato, Paulo RobertoFabrin, CarolineSubramanian, S. V.2023-07-29T13:59:15Z2023-07-29T13:59:15Z2022-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.ypmed.2022.107298Preventive Medicine, v. 164.1096-02600091-7435http://hdl.handle.net/11449/24898510.1016/j.ypmed.2022.1072982-s2.0-85139725242Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPreventive Medicineinfo:eu-repo/semantics/openAccess2023-07-29T13:59:15Zoai:repositorio.unesp.br:11449/248985Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:50:16.274756Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
title |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
spellingShingle |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases Boing, Antonio Fernando COVID-19 Epidemiology Inequalities in health |
title_short |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
title_full |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
title_fullStr |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
title_full_unstemmed |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
title_sort |
Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases |
author |
Boing, Antonio Fernando |
author_facet |
Boing, Antonio Fernando Boing, Alexandra Crispim Veras, Maria Amélia de Lacerda, Josimari Telino da Silva, Rafael Lopes Paixão Barbato, Paulo Roberto Fabrin, Caroline Subramanian, S. V. |
author_role |
author |
author2 |
Boing, Alexandra Crispim Veras, Maria Amélia de Lacerda, Josimari Telino da Silva, Rafael Lopes Paixão Barbato, Paulo Roberto Fabrin, Caroline Subramanian, S. V. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de Santa Catarina (UFSC) Faculdade de Ciências Médicas da Santa Casa de São Paulo Universidade do Estado de São Paulo Universidade Federal da Fronteira Sul Harvard University |
dc.contributor.author.fl_str_mv |
Boing, Antonio Fernando Boing, Alexandra Crispim Veras, Maria Amélia de Lacerda, Josimari Telino da Silva, Rafael Lopes Paixão Barbato, Paulo Roberto Fabrin, Caroline Subramanian, S. V. |
dc.subject.por.fl_str_mv |
COVID-19 Epidemiology Inequalities in health |
topic |
COVID-19 Epidemiology Inequalities in health |
description |
The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%–32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%–16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%–145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-01 2023-07-29T13:59:15Z 2023-07-29T13:59:15Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.ypmed.2022.107298 Preventive Medicine, v. 164. 1096-0260 0091-7435 http://hdl.handle.net/11449/248985 10.1016/j.ypmed.2022.107298 2-s2.0-85139725242 |
url |
http://dx.doi.org/10.1016/j.ypmed.2022.107298 http://hdl.handle.net/11449/248985 |
identifier_str_mv |
Preventive Medicine, v. 164. 1096-0260 0091-7435 10.1016/j.ypmed.2022.107298 2-s2.0-85139725242 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Preventive Medicine |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808129365127462912 |